<div dir="ltr"><div class="gmail_extra"><span style="font-family:arial,sans-serif;font-size:13px">Arjen,</span></div><div class="gmail_extra"><span style="font-family:arial,sans-serif;font-size:13px">Thanks, I reduced down the time resolution so computation can go faster. Now, m</span><span style="font-family:arial,sans-serif;font-size:13px">y matrix looks like this</span></div>
<div class="gmail_extra"><span style="font-family:arial,sans-serif;font-size:13px"><br></span></div><div class="gmail_extra"><div class="gmail_extra"><font face="arial, sans-serif">hpicomptimefreq = </font></div><div class="gmail_extra">
<font face="arial, sans-serif"><br></font></div><div class="gmail_extra"><font face="arial, sans-serif"> label: {204x1 cell}</font></div><div class="gmail_extra"><font face="arial, sans-serif"> dimord: 'rpt_chan_freq_time'</font></div>
<div class="gmail_extra"><font face="arial, sans-serif"> freq: [1x56 double]</font></div><div class="gmail_extra"><font face="arial, sans-serif"> time: [1x375 double]</font></div><div class="gmail_extra"><font face="arial, sans-serif"> powspctrm: [4-D double]</font></div>
<div class="gmail_extra"><font face="arial, sans-serif"> cumtapcnt: [59x56 double]</font></div><div class="gmail_extra"><font face="arial, sans-serif"> cfg: [1x1 struct]</font></div><div class="gmail_extra"><font face="arial, sans-serif"> trialinfo: [59x1 double]</font></div>
<div class="gmail_extra"><font face="arial, sans-serif"> beta: [4-D double]</font></div><div class="gmail_extra"><font face="arial, sans-serif"><br></font></div><div class="gmail_extra"><font face="arial, sans-serif">ft_regressconfound run on timelock data seems to return output with avg field. However, </font><span style="font-family:arial,sans-serif">ft_regressconfound run on frequency data, does not return average. I see the avg field being removed. Is there a reason?</span></div>
</div><div class="gmail_extra"><span style="font-family:arial,sans-serif;font-size:13px">Question - Since ft_regressconfound outputs power spectrum of individual trials - 4D matrix (instead of average), can I simply re-average the power spectrum over trials to see the average power for that subject. Also, I need to run grand average (over subjects) before running statistics. I hope these steps does not distort the data. Please advise.</span></div>
<div class="gmail_extra"><span style="font-family:arial,sans-serif;font-size:13px"><br></span></div><div class="gmail_extra"><span style="font-family:arial,sans-serif;font-size:13px">Thanks,</span></div><div class="gmail_extra">
<span style="font-family:arial,sans-serif;font-size:13px">Raghavan</span></div><div class="gmail_extra"><span style="font-family:arial,sans-serif;font-size:13px"><br></span></div><div class="gmail_extra"><br></div><div class="gmail_extra">
<span style="font-family:arial,sans-serif;font-size:13px"><br></span></div><div class="gmail_extra"><span style="font-family:arial,sans-serif;font-size:13px"><br></span></div><div class="gmail_extra"><span style="font-family:arial,sans-serif;font-size:13px"><br>
</span></div><div class="gmail_extra"><span style="font-family:arial,sans-serif;font-size:13px">Date: Wed, 19 Feb 2014 22:58:38 +0100 (CET)</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">From: "Stolk, A. (Arjen)" <</span><a href="mailto:a.stolk@fcdonders.ru.nl" style="font-family:arial,sans-serif;font-size:13px">a.stolk@fcdonders.ru.nl</a><span style="font-family:arial,sans-serif;font-size:13px">></span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">To: FieldTrip discussion list <</span><a href="mailto:fieldtrip@science.ru.nl" style="font-family:arial,sans-serif;font-size:13px">fieldtrip@science.ru.nl</a><span style="font-family:arial,sans-serif;font-size:13px">></span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">Subject: Re: [FieldTrip] regressconfound and frequency domain</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">Message-ID:</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px"> <</span><a href="mailto:2108167665.5423215.1392847118322.JavaMail.root@sculptor.zimbra.ru.nl" style="font-family:arial,sans-serif;font-size:13px">2108167665.5423215.1392847118322.JavaMail.root@sculptor.zimbra.ru.nl</a><span style="font-family:arial,sans-serif;font-size:13px">></span><br style="font-family:arial,sans-serif;font-size:13px">
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<span style="font-family:arial,sans-serif;font-size:13px">Dear Raghavan, Good to hear it's working out for you. A short answer would be 'no'. Reducing the size of your data matrix is likely going to speed up computations. Your time resolution seems pretty high (1500 frequency estimations per single trial); do you need that many? Yours, Arjen ----- Oorspronkelijk bericht -----</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> Van: "Raghavan Gopalakrishnan" <</span><a href="mailto:gopalar.ccf@gmail.com" style="font-family:arial,sans-serif;font-size:13px">gopalar.ccf@gmail.com</a><span style="font-family:arial,sans-serif;font-size:13px">></span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> Aan: </span><a href="mailto:fieldtrip@science.ru.nl" style="font-family:arial,sans-serif;font-size:13px">fieldtrip@science.ru.nl</a><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> Verzonden: Woensdag 19 februari 2014 22:01:00</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> Onderwerp: [FieldTrip] regressconfound and frequency domain</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> Arjen,</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> Thanks for answering all my previous questions. I was successfully</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> able to incorporate head movements to my erf data. As I understand I</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> have to do this separately for the time frequency data after keeping</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> individual trials. I am interested in both beta and gamma bands</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> [15:1:70]. my time frequency looks like this using wavelets,</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> timefreq =</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> label: {204x1 cell}</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> dimord: 'rpt_chan_freq_time'</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> freq: [1x56 double]</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> time: [1x1500 double]</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> powspctrm: [4-D double]</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> cumtapcnt: [55x56 double]</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> grad: [1x1 struct]</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> elec: [1x1 struct]</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> cfg: [1x1 struct]</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> trialinfo: [55x1 double]</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> After regressconfound</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> hpicomptimefreq =</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> label: {204x1 cell}</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> dimord: 'rpt_chan_freq_time'</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> freq: [1x56 double]</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> time: [1x1500 double]</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> powspctrm: [4-D double]</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> cumtapcnt: [55x56 double]</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> cfg: [1x1 struct]</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> trialinfo: [55x1 double]</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> beta: [4-D double]</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> Regressconfound took about 1 hr and 30 mins, since its a huge matrix</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> [55x204x56x1500]. I have 25 such blocks of data for 20 subjects. It</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> will take an enoumous amount of time to process the data through</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> regressconfound. Is there a workaround to make the processing faster</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> or am I missing something. Any help would be of great help.</span><br style="font-family:arial,sans-serif;font-size:13px"><span style="font-family:arial,sans-serif;font-size:13px">> Thanks,</span><br style="font-family:arial,sans-serif;font-size:13px">
<span style="font-family:arial,sans-serif;font-size:13px">> Raghavan</span><br></div></div>